Text Classification
setfit
Safetensors
sentence-transformers
xlm-roberta
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use Methni/STEMO-SetFit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use Methni/STEMO-SetFit with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("Methni/STEMO-SetFit") - sentence-transformers
How to use Methni/STEMO-SetFit with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Methni/STEMO-SetFit") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- af6ce3a5ada334708792c3def5b0135e882aef4ac6686c7fe7f652b26ba328b2
- Size of remote file:
- 37.8 kB
- SHA256:
- 4caf47fb4f883086b876dbfc88a513627e9ac9decf12a55f23ed0f526508bffc
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